Re-Identification Supervised Texture Generation. - Jian Wang 042; Yunshan Zhong; Yachun Li; Chi Zhang 026; Yichen Wei (CVPR, 2019)

Re-ID Driven Localization Refinement for Person Search. - Chuchu Han; Jiacheng Ye; Yunshan Zhong; Xin Tan 002; Chi Zhang 026; Changxin Gao; Nong Sang (ICCV, 2019)

Fine-grained Data Distribution Alignment for Post-Training Quantization. - Yunshan Zhong; Mingbao Lin; Mengzhao Chen; Ke Li 015; Yunhang Shen; Fei Chao 001; Yongjian Wu 001; Feiyue Huang; Rongrong Ji (CoRR, 2021)

IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization. - Yunshan Zhong; Mingbao Lin; Gongrui Nan; Jianzhuang Liu; Baochang Zhang 001; Yonghong Tian 001; Rongrong Ji (CVPR, 2022)

Fine-grained Data Distribution Alignment for Post-Training Quantization. - Yunshan Zhong; Mingbao Lin; Mengzhao Chen; Ke Li 015; Yunhang Shen; Fei Chao 001; Yongjian Wu 001; Rongrong Ji (ECCV (11), 2022)

Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks. - Yunshan Zhong; Mingbao Lin; Xunchao Li; Ke Li 015; Yunhang Shen; Fei Chao 001; Yongjian Wu 001; Rongrong Ji (ECCV (18), 2022)

Exploiting the Partly Scratch-off Lottery Ticket for Quantization-Aware Training. - Yunshan Zhong; Mingbao Lin; Yuxin Zhang 002; Gongrui Nan; Fei Chao 001; Rongrong Ji (CoRR, 2022)

Shadow Removal by High-Quality Shadow Synthesis. - Yunshan Zhong; Mingbao Lin; Lizhou You; Yuxin Zhang 002; Luoqi Liu; Rongrong Ji (CoRR, 2022)

Bi-directional Masks for Efficient N: M Sparse Training. - Yuxin Zhang 002; Yiting Luo; Mingbao Lin; Yunshan Zhong; Jingjing Xie; Fei Chao 001; Rongrong Ji (ICML, 2023)

MultiQuant: A Novel Multi-Branch Topology Method for Arbitrary Bit-width Network Quantization. - Yunshan Zhong; Mingbao Lin; Yuyao Zhou; Mengzhao Chen; Yuxin Zhang 002; Fei Chao 001; Rongrong Ji (CoRR, 2023)

Spatial Re-parameterization for N: M Sparsity. - Yuxin Zhang 002; Mingbao Lin; Yunshan Zhong; Mengzhao Chen; Fei Chao 001; Rongrong Ji (CoRR, 2023)

I&S-ViT: An Inclusive & Stable Method for Pushing the Limit of Post-Training ViTs Quantization. - Yunshan Zhong; Jiawei Hu; Mingbao Lin; Mengzhao Chen; Rongrong Ji (CoRR, 2023)

Lottery Jackpots Exist in Pre-Trained Models. - Yuxin Zhang 002; Mingbao Lin; Yunshan Zhong; Fei Chao 001; Rongrong Ji (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Learning Image Demoiréing from Unpaired Real Data. - Yunshan Zhong; Yuyao Zhou; Yuxin Zhang 002; Fei Chao 001; Rongrong Ji (AAAI, 2024)

CaM: Cache Merging for Memory-efficient LLMs Inference. - Yuxin Zhang 002; Yuxuan Du; Gen Luo; Yunshan Zhong; Zhenyu Zhang 015; Shiwei Liu 003; Rongrong Ji (ICML, 2024)

ERQ: Error Reduction for Post-Training Quantization of Vision Transformers. - Yunshan Zhong; Jiawei Hu; You Huang; Yuxin Zhang 002; Rongrong Ji (ICML, 2024)

Semantics Prompting Data-Free Quantization for Low-Bit Vision Transformers. - Yunshan Zhong; Yuyao Zhou; Yuxin Zhang 002; Shen Li; Yong Li; Fei Chao 001; Zhanpeng Zeng; Rongrong Ji (CoRR, 2024)

Distribution-flexible subset quantization for post-quantizing super-resolution networks. - Yunshan Zhong; Mingbao Lin; Jingjing Xie; Yuxin Zhang 002; Fei Chao 001; Rongrong Ji (Sci. China Inf. Sci., 2025)

MBQuant: A novel multi-branch topology method for arbitrary bit-width network quantization. - Yunshan Zhong; Yuyao Zhou; Fei Chao 001; Rongrong Ji (Pattern Recognit., 2025)

Towards Accurate Post-Training Quantization of Vision Transformers via Error Reduction. - Yunshan Zhong; You Huang; Jiawei Hu; Yuxin Zhang 002; Rongrong Ji (IEEE Trans. Pattern Anal. Mach. Intell., 2025)